Senior Staff ML Engineer: Fraud Prevention & Trust Systems

Uber; Seattle (WA); On-site; USD 267,000 - 297,000; Full time

Benefits offered by this job

Bonus program

Equity award

401(k) plan

Job summary

Uber is seeking a Senior Staff Machine Learning Engineer to join the Risk and Trust engineering organization. You will shape technical roadmaps, design robust ML solutions for fraud prevention and account integrity, and lead end-to-end ML product delivery at scale.

In this role, you will work on productionizing ML models, AB testing, and rollout strategies, while strengthening the team and cultivating talent. A strong background in ML methodologies and scalable data pipelines is essential.

Qualifications

• 10+ years of industry experience developing ML models and shipping to production.
• Master's degree in Computer Science, Engineering, Mathematics or related field.
• Strong problem-solving skills with expertise in ML methodologies.
• Experience applying ML, statistics, or optimization techniques to solve large-scale real-world problems.
• Experience with ML frameworks (TensorFlow, PyTorch, or JAX) and data pipelines; languages: Python, Spark SQL, Presto, Go, Java.

Responsibilities

• Shape the technical roadmap and problem formulations for the team with product and leadership.
• Apply ML, optimization, and statistics to design robust solutions impacting Uber's business.
• Elevate the MLE role and mentor talent within the organization.
• Own end-to-end ML product development: pipeline, system design, AB testing, rollout, and productionization.

Skills

ML expertise

Problem solving

Production ML

Algorithmic knowledge

Education

Master's degree

Tools

TensorFlow

PyTorch

JAX

Python

Spark SQL

Presto

Go

Java

Job description

Uber is seeking a Senior Staff Machine Learning Engineer to join the Risk and Trust engineering organization. You will shape technical roadmaps, design robust ML solutions for fraud prevention and account integrity, and lead end-to-end ML product delivery at scale.

In this role, you will work on productionizing ML models, AB testing, and rollout strategies, while strengthening the team and cultivating talent. A strong background in ML methodologies and scalable data pipelines is essential.